Title: IntersubjectiveStaking: A New Consensus System to Avoid Majority Tyranny
Introduction
During the May Day holiday, Eigenlayer released its EigenToken white paper. Strictly speaking, this is not a traditional economic white paper aimed at introducing incentive models and value in the traditional sense, but it brings a completely new business system—Intersubjectivestaking based on EigenToken. After reading the full white paper (without delving into the appendix) and the interpretations of predecessors, I have some thoughts and understanding of my own, which I hope to share with everyone and look forward to discussing. To start with the conclusion, I believe the significance of Intersubjectivestaking lies in proposing a consensus system based on a forkable ERC20 token model, which can be used to make decisions on some "intersubjective" issues and at the same time avoid the tyranny of the majority.
What is "Intersubjectivity"?
Understanding Intersubjective is a prerequisite for understanding the significance of this system. There seems to be no unified conclusion on how to translate this term on the Chinese internet. After reading an article by Professor Pan Zhixiong, I tend to agree that the concept of "social consensus" can be well used to understand its meaning. However, I feel that using "群体主观性" (intersubjectivity) to refer to this concept seems to be more in line with the literal translation, which is my understanding. Therefore, in the following text, I choose to use "群体主观性" to refer to Intersubjective.
So, what is "群体主观性"? In the context of EigenLayer, it refers to a broad consensus among all positive observer groups in a system on the right or wrong execution results of a certain transaction. This is called "intersubjective," which means group subjectivity. One of EigenLayer's core values is to decouple the consensus layer from the execution layer and focus on building and maintaining the former, thus making consensus service-oriented and reducing the development cost of Web3 applications, fully tapping into the potential market demand. In the white paper, EigenLayer seems to position itself as a decentralized digital public platform that can execute digital tasks for third parties, so it is necessary to analyze the boundaries of its services, that is, to clarify what types of digital tasks can be "trusted" for execution. In the context of Web3, "trusted" usually means a system designed by cryptography or economic models to avoid errors in the execution of digital tasks. Therefore, the first thing to do is to classify the possible execution errors of digital tasks. EigenLayer divides the execution errors of digital tasks into three categories:
Objective Attributable Errors: This category refers to errors that can be proven through a logical or mathematical deduction based on a set of objectively existing evidence (usually referring to on-chain data or data with DA) without relying on the trust of a specific entity. For example, in Ethereum, if a node signs two conflicting blocks, this error can be proven through cryptography. Similarly, this includes the fraud proof process in OPRollup, which re-executes a set of disputed data in the on-chain execution environment and can determine the error through result comparison.
Intersubjective Attributable Errors: This category refers to errors in which all participant groups in a system have a consistent subjective judgment standard for the execution results of a certain digital task. This type of error can be further divided into two categories:
- Errors that can be identified by backtracking past data at any time, for example, in a price oracle, if the spot price of BTC on Binance at 00:00:00 UTC on May 8, 2024, is $1, this error can be identified at any time after the fact.
- Errors that can only be observed in real-time, for example, malicious censorship, assuming a transaction is maliciously refused for a long time by a group of nodes.
Unattributable Errors: This category refers to errors that have not yet had a definite consensus judgment standard among the group, such as judging whether Paris is the most beautiful city, and so on.
IntersubjectiveStaking aims to effectively address digital tasks with intersubjective attributes, which means it can handle execution errors of the intersubjective attributable type of digital tasks. It can also be seen as an extension of the on-chain system.
The Problem of Majority Tyranny in Current Solutions
The so-called majority tyranny is a political term that refers to the situation where the vast majority of seats in a parliament jointly force through policies, thereby encroaching on the rights of the minority. After clarifying the goals of EigenLayer, let's take a look at the current types of solutions for such problems. According to EigenLayer's summary, they are broadly divided into two types:
Punishment Mechanism: This type of mechanism usually deters malicious behavior by penalizing staking funds of malicious nodes through cryptoeconomics. Stakingslash is one such mechanism. However, this method is prone to a problem. Imagine a scenario where an honest node submits evidence of wrongdoing, but at this time, the majority of nodes in the system decide to collude and engage in malicious behavior, they can choose to ignore the evidence, or even punish the honest node in reverse.
Committee Mechanism: This type of mechanism usually sets a fixed group of committee nodes, and in case of disputes, the accuracy of the evidence of wrongdoing is entrusted to the committee nodes. However, whether the committee is trustworthy becomes a major issue. When committee nodes collude in wrongdoing, the system is on the brink of collapse.
It is evident that both of these solutions encounter the problem of majority tyranny. This demonstrates the difficulty in solving such problems. Although there is a consistent judgment on the accuracy of the execution results, due to the lack of objective verification capability, trust shifts from cryptography or mathematics to human trust. However, when the majority chooses to engage in wrongdoing, the current solutions are powerless.
Avoiding Majority Tyranny through the Social Consensus Capability of Forkable Work Tokens
So, how does EigenLayer solve this problem? The answer lies in designing a forkable work token on-chain and using the social consensus capability brought by staking based on this work token to handle digital tasks with intersubjective attributes and avoid the problem of majority tyranny.
So, what exactly is the so-called social consensus capability brought by forkable work tokens, and how does it avoid the problem of majority tyranny? First, EigenLayer points out that the inspiration comes from the study of ETHPoS consensus. It believes that Ethereum's security comes from two aspects:
Cryptoeconomic Security: By requiring block-producing nodes to stake funds and designing punishment mechanisms for malicious behavior, the economic cost of wrongdoing exceeds the potential gains, thus eliminating malicious behavior.
Social Consensus: When the chain experiences a fork due to certain malicious behavior, due to the consistent judgment standard on the accuracy of the execution results, any honest or sincere user can choose the fork they believe is correct based on their subjective observation of different fork execution results. Therefore, even if malicious nodes control the majority of staked funds and the problem of majority tyranny arises, it will be accompanied by users abandoning the malicious fork, gradually making the value of the forked chain surpass the malicious chain. For example, most CEXs will choose the forked chain with correct but minimal staking support and abandon the malicious chain with substantial staking support. With widespread social consensus, the value of the malicious chain will gradually disappear, and the forked chain will become the "orthodox fork" again.
We know that the essence of blockchain is to achieve consensus on the order of a set of transactions in a trustless distributed system. Ethereum has designed a serial execution environment, EVM, based on this, so when transactions are consistent, EVM will achieve consistent execution results. EigenLayer believes that the evaluation of the execution results of such transactions is mostly objectively attributable, but there are also cases of intersubjective attributability. Specifically, this refers to the evaluation of chain liveness. In Ethereum's PoS consensus mechanism, there is a special Inactivity Leak mode. When unknown circumstances cause more than 1/3 of the nodes to be unable to produce blocks correctly, the cryptoeconomic security of PoS will be compromised. An extreme example is when a region's internet is disrupted due to war. In this case, Ethereum will experience a fork. When the consensus mechanism detects this situation, it will enter Inactivity Leak mode, and new block production will not be rewarded with inflation rewards. At the same time, inactive nodes will gradually be slashed until the staked funds of active nodes exceed 2/3 again. This will gradually restore the cryptoeconomic security of the two forked chains.
After this, which chain will become the so-called "orthodox fork" can only rely on users' active choices based on their own judgment standards. This process is "social consensus." With users' active choices, the value of the two forked chains will shift until one fork achieves a clear victory in the competition for cryptoeconomic security. This process can be seen as security endowed by social consensus.
In summary, EigenLayer believes that Ethereum relies on social consensus to identify and resolve intersubjective errors related to chain consistency, known as chain liveness attacks. The core of this social consensus capability comes from forking. When disagreements arise, instead of immediately determining which side is acting maliciously, it relies on subsequent users' "voting with their feet" to resolve the disagreement through the ability of social consensus. This avoids the problem of the protocol being subjected to majority tyranny because honest nodes will not be immediately penalized by collusion, giving them the ability to rise again. This approach demonstrates its value in addressing intersubjective errors.
Therefore, following this judgment, EigenLayer has referenced and upgraded a consensus model called Augur, an on-chain prediction market protocol, and proposed a forkable work token named EIGEN. Around EIGEN, they have designed an Intersubjective staking mechanism to address the execution consensus of digital tasks with intersubjective attributes. When there is a disagreement on the execution results, conflicts are resolved through forking EIGEN and relying on social consensus within subsequent time windows. The specific technology is not actually complicated and has been discussed in some articles, so I won't go into it here. I believe that understanding the above relationship can help grasp the significance or value of Eigen intersubjective staking.
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